Digital subtraction angiography (DSA) is a well-known imaging technique, which may be used to visualize blood vessels of a patient in medical imaging. In a classical workflow, first a mask image data set without a contrast agent being present in the region of interest is acquired by x-ray imaging. In this mask image data set, blood vessels may hardly be distinguished from surrounding anatomical structures. Subsequently, a filled image data set of the region of interest is acquired with contrast agent being present in the blood vessels of the region of interest. In these x-ray images, the blood vessels are amplified, whereas the contrast of anatomical structures surrounding the contrast-enhanced blood vessels remains constant. To derive a DSA angiography image data set, the mask image data set, (e.g., the non-contrast-enhanced image), is subtracted from the filled image data set, (e.g., the contrast enhanced image data set). In this manner, the signal from surrounding anatomical structures, (e.g., tissue and bones), may be eliminated and the resulting image only shows the blood vessels. Digital subtraction angiography may be performed using three-dimensional image data sets, e.g., computer tomography (CT) image data sets and/or using two-dimensional image data sets such as projection images. In the case of projection images, the line integral of the mask image data set and the filled (e.g., contrast-enhanced) image data set are subtracted and the attenuation of the contrast-enhanced vessels may be obtained.
A known problem in digital subtraction angiography is the time difference between the acquisition of the mask image data set and the filled image data set, which makes this imaging technique prone to motion errors. It has thus been proposed to perform registration of the mask image data set and the filled image data set, like for example described in U.S. Pat. No. 8,023,732 and Y. Bentoutou et al., “An invariant approach for image registration in digital subtraction angiography”, Pattern Recognition 35 (12) 2002, pages 2853-2865. Because blood vessels are soft-tissue structures, the appearing deformations are mostly of a non-rigid nature, complicating the process of registration. An additional problem is the time-consuming nature of the registration itself, which may not be desirable if the digital subtraction angiography is performed during an in particular minimally invasive intervention.
Another problem related to digital subtraction angiography is radiation exposure of the patient. To obtain one DSA angiography image data set, the patient is irradiated at least two times.
In an article by M. Unberath et al., “Virtual single-frame subtraction imaging”, proceedings of the 4th CT Meeting (4th International Conference on Image Formation in X-Ray Computed Tomography), Bamberg, Germany, Jul. 18, 2016, pages 89 to 92, 2016, a virtual digital subtraction coronary angiography has been proposed. By vessel segmentation and background estimation, a virtual mask image useable for subtraction may be derived. However, assumptions and time-consuming image analysis are required, which may lead to inaccuracies and/or errors in the virtual mask image data set.